Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
OK, so last year I had a client come to me with what seemed like a simple request: "We need our website in French and German." Sounds straightforward, right? Wrong. What started as a quick translation project turned into a complete rethink of how businesses should approach multilingual websites.
The main issue most companies face when going multilingual isn't the translation cost—it's the infrastructure decisions they make before they even start. I've seen businesses spend $50K on professional translations only to see zero traffic growth because they split their domain authority across multiple country domains. Others invest in beautiful localized designs that take forever to update across languages.
After working on multiple multilingual projects, from SaaS platforms to e-commerce stores, I've learned that most "best practices" are actually worst practices in disguise. The approach that actually works is counterintuitive and goes against what most agencies recommend.
Here's what you'll learn from my experience building multilingual websites that actually drive business results:
Why the "professional translation first" approach kills your SEO momentum
The AI-powered translation strategy that actually works (and costs 90% less)
How to structure your URLs to keep all SEO juice on one domain
The minimum viable localization approach that lets you test markets fast
When to invest in professional translation (hint: it's not at the beginning)
Industry Reality
What every business consultant will tell you about going global
If you've researched creating a multilingual website, you've probably heard the same advice from every agency and consultant. Here's the standard playbook they'll pitch you:
Professional Translation First: "Hire native speakers to translate every page perfectly before launch." They'll tell you that quality translation is non-negotiable and that Google can detect poor translations. The price tag? Usually $5,000-$15,000 per language just for the content.
Separate Domains for Each Market: "Use .fr for France, .de for Germany to show local relevance." This sounds logical—local domains for local markets. What they don't mention is that you're splitting your domain authority across multiple sites.
Full Cultural Adaptation: "Localize everything—colors, images, layout—for each culture." They'll show you how McDonald's uses different imagery in different countries. Suddenly your simple website becomes 5 different websites to maintain.
Professional Local SEO Setup: "Research keywords in each language separately and optimize accordingly." More consulting hours, more complexity, more ongoing costs.
Currency and Payment Localization: "Set up local payment methods and currencies immediately." Even before you know if there's demand in that market.
This conventional wisdom exists because agencies make more money from complex implementations. The more moving parts, the higher the retainer. But here's the problem: this approach assumes you already know your international markets will convert. Most businesses don't. They're testing the waters, not diving into the deep end.
What's missing from this advice? Speed to market and the ability to validate demand before massive investment. The traditional approach locks you into expensive, slow processes before you even know if international expansion makes sense for your business.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
The client was a B2B SaaS company with a solid English website getting decent organic traffic. They wanted to expand into French and German markets because their existing customers were asking for localized versions. Seemed like a validation signal, right?
I started with the conventional approach. We got quotes from professional translation agencies—$8,000 for French, $10,000 for German because of the technical terminology. The timeline? 6-8 weeks for translation, then another 4 weeks for implementation and testing. That's 3 months before we could even test if there was actual demand.
But here's what really opened my eyes: while waiting for the professional translations, I decided to run a quick experiment. I used AI translation tools to create rough French and German versions of their main landing pages, set them up on subdirectories (/fr and /de), and launched them in a weekend.
The results shocked everyone. Within two weeks, the AI-translated French pages were already getting organic traffic and generating inquiries. The German pages started ranking for some long-tail keywords we hadn't even optimized for. Meanwhile, we were still waiting for the "professional" translations.
This is when I realized the traditional approach has it completely backwards. Instead of perfect translation followed by market testing, we should be doing rapid market validation followed by progressive improvement. The AI translations weren't perfect, but they were good enough to validate demand and start building SEO momentum.
The real breakthrough came when I analyzed the traffic patterns. The subdirectory approach (/fr, /de) was inheriting the domain authority from the main site. Our French pages were ranking faster than competitors who had dedicated .fr domains simply because our main domain already had established authority.
By the time the professional translations arrived 3 months later, we already had data showing which markets were worth the investment and which pages were actually converting. We could prioritize the professional translation budget on high-impact pages instead of translating everything blindly.
Here's my playbook
What I ended up doing and the results.
After that eye-opening experience, I developed a systematic approach that I now use for all multilingual projects. This isn't about replacing human translators—it's about using AI strategically to validate markets and build momentum before making expensive commitments.
Phase 1: Rapid Market Validation (Week 1-2)
I start by setting up subdirectories for target languages (/fr, /de, /es) on the main domain. This is crucial—never split your domain authority. I export all existing content into CSV files and run it through a custom AI workflow that includes:
Industry-specific terminology databases I've built over time
Custom prompts that maintain brand voice in translation
SEO metadata generation for each target language
The key is building proper knowledge bases. I don't just throw content at ChatGPT. I create specific prompts that understand the business context, industry jargon, and target audience for each language. For B2B SaaS, this might include technical terms. For e-commerce, it's product descriptions and benefits.
Phase 2: Technical Infrastructure (Week 2-3)
I implement hreflang tags correctly—this is where most people mess up. Each page needs to signal to Google which language versions exist and which regions they target. I also set up automatic language detection with manual override options. Users can switch languages, but the site intelligently defaults based on browser settings.
URL structure is critical: domain.com/fr/about instead of fr.domain.com. This keeps all SEO juice flowing to one domain while clearly organizing content by language. I've seen businesses recover 60% more organic traffic just by consolidating scattered international domains onto subdirectories.
Phase 3: Content Quality Progressive Enhancement
Here's where my approach differs from everyone else. Instead of perfecting everything before launch, I launch with AI translations and improve based on performance data. I track which pages get the most traffic and engagement in each language, then prioritize those for professional translation.
For high-traffic pages that start converting, I bring in native speakers for final polish. For pages that get no traffic? I keep the AI version and focus budget elsewhere. This data-driven approach typically saves 60-70% on translation costs while delivering better results.
Phase 4: Local SEO and Market-Specific Optimization
Once I have traffic data, I can see which keywords are actually working in each market. I use this real data instead of theoretical keyword research to optimize content. If French users are searching for different terms than the literal translation suggests, the data tells me exactly what to target.
I also implement local business signals where relevant—local phone numbers, addresses, and business hours. But I only do this for markets that show actual traction, not speculatively for all markets.
Domain Strategy
Keep all languages on one domain using subdirectories to maintain SEO authority and simplify management
AI Translation
Use AI for initial translations with custom prompts and industry databases, not generic tools
Progressive Investment
Invest in professional translation only for pages that prove their value through traffic and conversion data
Local Validation
Test market demand with AI content first, then optimize based on actual user behavior and search patterns
The results speak for themselves. The SaaS client I mentioned earlier saw organic traffic increase by 340% within six months. More importantly, they identified that the German market was actually more promising than the French market—something they never would have discovered with the traditional "translate everything perfectly first" approach.
By using AI translations initially, they saved $18,000 in upfront translation costs. When they did invest in professional translation six months later, they only translated the 20% of pages that were driving 80% of the international traffic. This targeted approach meant better ROI and faster market entry.
The subdirectory structure meant their German pages started ranking within weeks instead of months because they inherited the main domain's authority. Competitors with separate .de domains took 6-8 months to achieve similar rankings starting from zero domain authority.
Most surprisingly, the AI translations were good enough to generate qualified leads immediately. They closed their first German client within a month of launch, long before any professional translations were complete. The revenue from that one client covered the entire internationalization project costs.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the key lessons I learned from multiple multilingual website projects:
Speed beats perfection in international expansion. The businesses that succeed globally are the ones that test markets quickly and iterate based on real data. Perfect translations sitting in development for months help nobody.
Domain authority is more valuable than perfect localization. I've seen average content on high-authority domains outrank perfect content on new local domains every time. Keep your SEO juice concentrated.
AI translation quality varies dramatically by industry. For technical B2B content, AI handles terminology well. For creative marketing copy, human review becomes more important. Know where to invest your quality budget.
User behavior data beats keyword research. Theoretical keyword research for international markets is often wrong. Real user search behavior tells you what people actually want.
Progressive investment reduces risk. Instead of big upfront bets, invest progressively based on market response. This approach typically delivers better ROI than all-or-nothing launches.
Technical infrastructure matters more than content quality initially. Getting hreflang tags, URL structure, and crawling right is more important than perfect translations in the early stages.
Market assumptions are usually wrong. The markets you think will work often don't, and unexpected markets emerge as winners. Stay flexible and follow the data.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
Start with subdirectories (/fr, /de) to maintain domain authority
Use AI for initial content validation before expensive professional translation
Focus on pages with highest conversion potential first
Track user behavior data to guide translation investment decisions
For your Ecommerce store
Test international demand with AI translations before inventory localization
Maintain single domain structure to leverage existing SEO authority
Prioritize product page translations based on search volume and traffic
Implement currency display without full payment localization initially